This paper describes the Integrated Diagnostic System (IDS), an applied
AI project concerned with the development of hybrid information systems
to diagnose problems and help manage repair processes of commercial
aircraft fleets. A study at one major airline indicated that significant
benefits could accrue (approximately 2% of overall maintenance budget)
through the use of innovative information technology. The IDS prototype
(currently in extended field trial) takes as input a stream of messages
representing maintenance and diagnostic events. These are filtered and
aggregated in order to yield information in an appropriate form for
various decision making tasks (and in particular for the maintenance
staff while performing fault isolation and repair procedures). IDS was
built using ART*Enterprise and makes extensive use of its rule-based
and case-based reasoning facilities in order to apply various sources of
knowledge (manuals, heuristics, historical data) to this problem. As
well as technical issues, this paper discusses the motivation for, and
methodology followed in this project.

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.